Subgroup-Specific Symptom Cluster Experience Profiles in Childhood Cancer Survivors

2.50
Hdl Handle:
http://hdl.handle.net/10755/160787
Type:
Presentation
Title:
Subgroup-Specific Symptom Cluster Experience Profiles in Childhood Cancer Survivors
Abstract:
Subgroup-Specific Symptom Cluster Experience Profiles in Childhood Cancer Survivors
Conference Sponsor:Midwest Nursing Research Society
Conference Year:2009
Author:Finnegan, Lorna, PhD
P.I. Institution Name:University of Illinois at Chicago
Title:College of Nursing
Contact Address:845 S. Damen Avenue, MC 802, Chicago, IL, 60612, USA
Contact Telephone:312-996-1668
Co-Authors:L. Finnegan, College of Nursing, University of Illinois at Chicago, Chicago, IL;
Purpose: For most childhood cancers, aggressive medical treatments have led to 80% 5-year survival rates, resulting in more than 300,000 childhood cancer survivors in the United States. Although most adult survivors of childhood cancers (ACC-survivors) are cancer free, as many as 40% still experience a myriad of troubling symptoms. The purpose of this study is to characterize unique subgroups of ACC-survivors based on their profiles of experiencing a five-symptom cluster of pain, fatigue, sleep disturbance, psychological distress, and difficulty concentrating. We will also analyze selected risk and protective factors for their influence on further specifying the subgroup-specific symptom cluster experience profiles. Conceptual framework, participants, and methods: We developed a conceptual model based on findings from preliminary studies, existing literature on risk and protective factors that influence symptoms in ACC-survivors, and the Wilson and Cleary model of health-related QoL. Using existing data from the Childhood Cancer Survivor Study, the world's largest multi-institutional long-term follow-up study of childhood cancer survivors, we will use latent variable mixture modeling to empirically identify ACC-survivor subgroups. Measures include subscales from the Medical Outcomes Survey Short Form-36 and the Brief Symptom Inventory-18, along with multiple questions regarding chronic health conditions, lifestyle variables (physical activity, smoking status, body mass index and alcohol use), and sociodemographic variables. We will also use medical record data on cancer types, cancer treatment modalities, and age at cancer diagnosis. Results: The mixture models will include distinct subgroups of ACC-survivors with unique symptom cluster experience profiles: high symptoms, low symptoms, and mixed symptoms. Each subgroup will be characterized by a unique risk and protective factor profile. Conclusions: Further development and validation of these subgroup-specific symptom cluster experience profiles, as defined by risk and protective factors, will strengthen the potential to identify ACC-survivors most in need of targeted nursing interventions to alleviate symptoms.
Repository Posting Date:
26-Oct-2011
Date of Publication:
17-Oct-2011
Sponsors:
Midwest Nursing Research Society

Full metadata record

DC FieldValue Language
dc.typePresentationen_GB
dc.titleSubgroup-Specific Symptom Cluster Experience Profiles in Childhood Cancer Survivorsen_GB
dc.identifier.urihttp://hdl.handle.net/10755/160787-
dc.description.abstract<table><tr><td colspan="2" class="item-title">Subgroup-Specific Symptom Cluster Experience Profiles in Childhood Cancer Survivors</td></tr><tr class="item-sponsor"><td class="label">Conference Sponsor:</td><td class="value">Midwest Nursing Research Society</td></tr><tr class="item-year"><td class="label">Conference Year:</td><td class="value">2009</td></tr><tr class="item-author"><td class="label">Author:</td><td class="value">Finnegan, Lorna, PhD</td></tr><tr class="item-institute"><td class="label">P.I. Institution Name:</td><td class="value">University of Illinois at Chicago</td></tr><tr class="item-author-title"><td class="label">Title:</td><td class="value">College of Nursing</td></tr><tr class="item-address"><td class="label">Contact Address:</td><td class="value">845 S. Damen Avenue, MC 802, Chicago, IL, 60612, USA</td></tr><tr class="item-phone"><td class="label">Contact Telephone:</td><td class="value">312-996-1668</td></tr><tr class="item-email"><td class="label">Email:</td><td class="value">lornaf@uic.edu</td></tr><tr class="item-co-authors"><td class="label">Co-Authors:</td><td class="value">L. Finnegan, College of Nursing, University of Illinois at Chicago, Chicago, IL;</td></tr><tr><td colspan="2" class="item-abstract">Purpose: For most childhood cancers, aggressive medical treatments have led to 80% 5-year survival rates, resulting in more than 300,000 childhood cancer survivors in the United States. Although most adult survivors of childhood cancers (ACC-survivors) are cancer free, as many as 40% still experience a myriad of troubling symptoms. The purpose of this study is to characterize unique subgroups of ACC-survivors based on their profiles of experiencing a five-symptom cluster of pain, fatigue, sleep disturbance, psychological distress, and difficulty concentrating. We will also analyze selected risk and protective factors for their influence on further specifying the subgroup-specific symptom cluster experience profiles. Conceptual framework, participants, and methods: We developed a conceptual model based on findings from preliminary studies, existing literature on risk and protective factors that influence symptoms in ACC-survivors, and the Wilson and Cleary model of health-related QoL. Using existing data from the Childhood Cancer Survivor Study, the world's largest multi-institutional long-term follow-up study of childhood cancer survivors, we will use latent variable mixture modeling to empirically identify ACC-survivor subgroups. Measures include subscales from the Medical Outcomes Survey Short Form-36 and the Brief Symptom Inventory-18, along with multiple questions regarding chronic health conditions, lifestyle variables (physical activity, smoking status, body mass index and alcohol use), and sociodemographic variables. We will also use medical record data on cancer types, cancer treatment modalities, and age at cancer diagnosis. Results: The mixture models will include distinct subgroups of ACC-survivors with unique symptom cluster experience profiles: high symptoms, low symptoms, and mixed symptoms. Each subgroup will be characterized by a unique risk and protective factor profile. Conclusions: Further development and validation of these subgroup-specific symptom cluster experience profiles, as defined by risk and protective factors, will strengthen the potential to identify ACC-survivors most in need of targeted nursing interventions to alleviate symptoms.</td></tr></table>en_GB
dc.date.available2011-10-26T23:10:39Z-
dc.date.issued2011-10-17en_GB
dc.date.accessioned2011-10-26T23:10:39Z-
dc.description.sponsorshipMidwest Nursing Research Societyen_GB
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